Multi-Agent Coordination

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Multi-agent coordination studies how agents with partial information, different capabilities, or competing incentives can act together in settings such as robot teams, traffic networks, resource allocation, and language-model workflows. Common approaches include decentralized and centralized multi-agent reinforcement learning, game-theoretic planning, role and task assignment, and communication through messages, shared memory, or learned coordination policies. Recent work also develops orchestration protocols and benchmarks for language-model agents, measuring not just task success but information use, role adherence, safety, and coordination failures. A central tension is that communication and additional agents can improve complex teamwork but also introduce overhead, propagate errors, or make performance worse; individual reasoning ability alone does not guarantee effective cooperation.

Latest papers

520 papers84 papers in the last four weeks, up 91% on the four weeks before. 0.5% of all new papers.

Scale-Dependent Collective Adaptation in Self-Amending LLM Societies: A Cross-Family Study of Emergent Governance
May 17, 2026Kazuya Horibe, Masaomi Hatakeyama, Gen Masumoto +2Multi-Agent LLM Systems Multi-Agent Coordination
Center for Brain Science, RIKEN. · Department of Evolutionary Biology and Environmental Studies, University of Zurich. · Information R&D and Strategy Headquarters. +3
Taming "Zombie'' Agents: A Markov State-Aware Framework for Resilient Multi-Agent Evolution
May 17, 2026Taolin Zhang, Pukun Zhao, Qizhou Chen +5Multi-Agent LLM Systems Multi-Agent Coordination
School of Computer Science and Information Engineering, Hefei University of Technology · Guangdong University of Finance and Economics · East China Normal University +1
Bimodal Synchronization Performance: Why Noise and Sparse Connectivity Can Improve Collective Timing
May 17, 2026Till Aust, Tianfu Zhang, Andreagiovanni Reina +1Dynamical Systems Multi-Agent Coordination
Department of Computer and Information Science, University of Konstanz, Konstanz, Germany · Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany · Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany
NeuroMAS: Multi-Agent Systems as Neural Networks with Joint Reinforcement Learning
May 16, 2026Haoran Lu, Luyang Fang, Wenxuan Zhong +1Multi-Agent LLM Systems Multi-Agent Coordination
Department of Statistics, University of Georgia, Athens, GA 30602
Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models
May 15, 2026Xingjian Wu, Junkai Lu, Siyu Yan +4Multi-Agent Coordination Multi-Agent Systems
East China Normal University
Beyond Partner Diversity: An Influence-Based Team Steering Framework for Zero-Shot Human-Machine Teaming
May 14, 2026Wei Sheng, Rohan PalejaMulti-Agent Coordination Cooperative MARL
Department of Computer Science Purdue University
Temporal Fair Division in Multi-Agent Systems: From Precise Alternation Metrics to Scalable Coordination Proxies
May 14, 2026Nikolaos Al. Papadopoulos, Ismael Tito Freire, Marti Sanchez-Fibla +1Multi-Agent Coordination Fair Resource Allocation
University of Macedonia, Department of Applied Informatics, Thessaloniki, Greece · Sorbonne Université, Institut des Systèmes Intelligents et de Robotique (ISIR), Paris, France · Universitat Pompeu Fabra, Department of Information and Communication Technologies, Barcelona, Spain
Agentic AI Ecosystems in Higher Education: A Perspective on AI Agents to Emerging Inclusive, Agentic Multi-Agent AI Framework for Learning, Teaching and Institutional Intelligence
May 14, 2026Vidya K Sudarshan, Anushka Sisodia, Reshma A Ramachandra +2Multi-Agent Coordination AI in Education
College of Computing and Data Science, Nanyang Technological University, NTU, Singapore · DeepMed Ptd Ltd, India
Decoupled Planning for Multiple Omega-Regular Objectives
May 13, 2026Guy Avni, Thomas A. Henzinger, Kaushik Mallik +2Multi-Agent Coordination Graph-Based Planning
Department of Computer Science, University of Haifa, Israel · Institute of Science and Technology Austria, Klosterneuberg, Austria · IMDEA Software Institute, Spain +2
When Does Hierarchy Help? Benchmarking Agent Coordination in Event-Driven Industrial Scheduling
May 13, 2026Ziqi Wang, Yuhao Yang, Zhiwei Ling +2Multi-Agent Coordination
Zhejiang University
Embodied Multi-Agent Coordination by Aligning World Models Through Dialogue
May 13, 2026Vardhan Dongre, Dilek Hakkani-TürMulti-Agent Coordination AI Agent Benchmarks
Siebel School of Computing & Data Science University of Illinois Urbana-Champaign
Ready from Day 1: Population-Aware Coordination for Large-Scale Constrained Multi-Agent Systems
May 12, 2026Angel Wang, Dominique Perrault-Joncas, Alvaro Maggiar +2Multi-Agent System Optimization Multi-Agent Coordination
Amazon
LIDSA: Cognitive Arbitration for Signal-Free Autonomous Intersection Management
May 12, 2026Abderrahmane Lakas, Mohamed Amine Ferrag, Merouane DebbahMulti-Agent Coordination Language Model-Based Control
Department of Computer and Network Engineering, United Arab Emirates University, UAE · Research Institute for Digital Future, Khalifa University, UAE
Shaping Zero-Shot Coordination via State Blocking
May 12, 2026Mingu Kang, Sunwoo Lee, Yonghyeon Jo +1Multi-Agent Coordination Cooperative MARL
Graduate School of Artificial Intelligence UNIST Ulsan, South Korea 44919
Distance-Constrained Unlabeled Multi-Agent Pathfinding
May 12, 2026Takahiro Suzuki, Yuma Tamura, Keisuke OkumuraConstrained Motion Planning Multi-Agent Coordination
Tohoku University · National Institute of Advanced Industrial Science and Technology (AIST)
Coordinated Diffusion: Generating Multi-Agent Behavior Without Multi-Agent Demonstrations
May 12, 2026Lasse Peters, Laura Ferranti, Andrea Bajcsy +1Multi-Agent Coordination Diffusion Policy
University of California, Berkeley · Delft University of Technology · Carnegie Mellon University
LLM-X: A Scalable Negotiation-Oriented Exchange for Communication Among Personal LLM Agents
May 12, 2026Giuliano Lorenzoni, Paulo Alencar, Donald CowanMulti-Agent LLM Systems Multi-Agent Coordination
University of Waterloo · University of Waterloo Waterloo, ON, Canada
Effect of Graph Gluing on Consensus in Networked Multi-Agent Systems
May 11, 2026Rohollah Moghadam, Santosh KandelMulti-Agent Coordination Multi-Agent Systems
Department of Electrical and Electronic Engineering, California State University-Sacramento, 5028 Riverside Hall, 6000 J Street, Sacramento, CA, 95819, USA · Department of Mathematics and Statistics, California State University-Sacramento, 226 Brighton Hall, 6000 J Street, Sacramento, CA, 95819, USA
Collective Alignment in LLM Multi-Agent Systems: Disentangling Bias from Cooperation via Statistical Physics
May 11, 2026Cristiano De NobiliMulti-Agent LLM Systems Multi-Agent Coordination
Critiqality, Milan, Italy
Towards Autonomous Railway Operations: A Semi-Hierarchical Deep Reinforcement Learning Approach to the Vehicle Rescheduling Problem
May 11, 2026Alberto Castagna, Stefan Zahlner, Adrian Egli +4Multi-Agent Coordination Intelligent Transportation Systems
∗enliteAI, AT · †SBB CFF FFS, CH · ‡Flatland Association, CH
Swarm Skills: A Portable, Self-Evolving Multi-Agent System Specification for Coordination Engineering
May 11, 2026Xinyu Zhang, Zhicheng Dou, Deyang Li +10Multi-Agent Coordination Multi-Agent Orchestration
openJiuwen Team & Gaoling School of Artificial Intelligence, Renmin University of China
EnactToM: An Evolving Benchmark for Functional Theory of Mind in Embodied Agents
May 11, 2026Gurusha Juneja, Dylan Lu, Saaket Agashe +7Multi-Agent Coordination Theory of Mind
University of California, Santa Barbara · 2King’s College London · 3Cisco Research
CalBench: Evaluating Coordination-Privacy Trade-offs in Multi-Agent LLMs
May 10, 2026Chelsea Zou, Yiheng Yao, Selena She +2Multi-Agent LLM Systems Multi-Agent Coordination
Stanford University
Robust Multi-Agent LLMs under Byzantine Faults
May 9, 2026Haejoon Lee, Vincent-Daniel Yun, Dimitra Panagou +1Multi-Agent LLM Systems Multi-Agent Coordination
Department of Robotics, University of Michigan, Ann Arbor, USA · Thomas Lord Department of Computer Science, University of Southern California, USA
HULK: Large-scale Hierarchical Coordination under Continual and Uncertain Temporal Tasks
May 9, 2026Qingyuan Luo, Jie Li, Meng GuoMulti-Agent Coordination Hierarchical Planning
the Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing 100871, China · National University of Defense Technology, Hunan 410073, China
Iterative Critique-and-Routing Controller for Multi-Agent Systems with Heterogeneous LLMs
May 9, 2026Wenzhi Fang, Liangqi Yuan, Guangchen Lan +2Multi-Agent LLM Systems Multi-Agent Coordination
Purdue University · Yonsei University
Too Many Specialists: Emergent Inefficiencies and Bottlenecks for Multi-agent Ad-hoc Collaboration
May 8, 2026Benjamin Panny, Shashank Mehrotra, Zahra Zahedi +2Multi-Agent Coordination Multi-Agent Collaboration
University of Pittsburgh Pittsburgh, PA, United States · Honda Research Institute USA, Inc. San Jose, CA, United States
SACHI: Structured Agent Coordination via Holistic Information Integration in Multi-Agent Reinforcement Learning
May 8, 2026Nikunj Gupta, James Zachary Hare, Jesse Milzman +2Multi-Agent Coordination Partially Observable RL
University of Southern California, Los Angeles, CA, USA · DEVCOM Army Research Laboratory, Adelphi, MD, USA · DEVCOM Army Research Office, Research Triangle Park, North Carolina, USA
TraceFix: Repairing Agent Coordination Protocols with TLA+ Counterexamples
May 8, 2026Shuren Xia, Qiwei Li, Taqiya Ehsan +1Multi-Agent LLM Systems Multi-Agent Coordination
Rutgers University Piscataway, NJ, USA
Alternating Target-Path Planning for Scalable Multi-Agent Coordination
May 8, 2026Yu Kumagai, Keisuke OkumuraMulti-Agent Coordination Multi-Robot Task Allocation
1Hitotsubashi University, Japan · 2National Institute of Advanced Industrial Science and Technology (AIST), Japan

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Scale-Dependent Collective Adaptation in Self-Amending LLM Societies: A Cross-Family Study of Emergent Governance

Kazuya Horibe, Masaomi Hatakeyama, Gen Masumoto, Takashi Hashimoto+1

Center for Brain Science, RIKEN. · Department of Evolutionary Biology and Environmental Studies, University of Zurich. · Information R&D and Strategy Headquarters.+3

Multi-Agent LLM Systems Multi-Agent Coordination Language Model Scaling Laws Emergent Behavior in Multi-Agent Systems

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We study group decision-making in artificial societies where the rules of play are themselves subject to collective amendment. Using the self-amending game Nomic, we compare multiple scales across two LLM families and find that collective adaptation does not improve monotonically with model size. Instead, both families exhibit a narrow mid-scale regime that supports sustained rule adoption, diverse amendments, and balanced consensus. Smaller models tend to remain rule-inert, whereas larger models often converge on restrictive voting patterns, and heterogeneous mixed-size groups collapse into veto-driven gridlock. These cross-scale contrasts persist under temperature perturbations and under a shift from unanimity to majority voting, although latent-state structure varies by family and scale. Hidden-state divergence alone does not explain collective performance: high representational divergence can coincide with poor behavioural outcomes. Linear probes reveal regime-selective coupling between latent vote-predictive signals and collective behaviour, but decodability is necessary rather than sufficient for adaptive play. Overall, the recurring regularity is non-monotonicity, not the particular scale at which the optimum appears. Self-amending games therefore provide a controlled testbed for studying collective adaptation in artificial societies beyond raw model scale.